Revolutionizing Pediatric Neurophysiology With Magnetoencephalography
Bibliographic record
Abstract
This paper considers the current and future use of magnetoencephalography (MEG) for assessing neural activity in children (birth to 18 years old), including the well-established use of SQUID (Superconducting QUantum Interference Device) MEG technology as well as the very rapidly developing Optically Pumped Magnetometry (OPM) technology. A primary conclusion is that the changing landscape of pediatric neurophysiology studies foretells a revolution in electromagnetic neuroimaging. These changes will produce some discontinuity, progressing away from what once worked well enough, namely, examining neural activity at the level of the EEG or MEG sensor, but is not up to current and anticipated challenges. Given features intrinsic to MEG, including simpler mathematical models for source localization and higher-dimensional representation of neural activity, little effect of open fontanelles and sutures on infant neural measures, and reference-free neural measures, MEG will often be the preferred method for assessing neural activity in children. In particular, noninvasive, whole-brain MEG sensor data with source localization provide measures of neural activity in brain space that richly represent the structure and maturation of neural activity spanning both local and regional processes, as well as measures of connectivity within and between brain regions. Assessing neurophysiology in brain space is also essential for associating local neural activity with local brain structure (e.g., gray and white matter) and brain chemistry (e.g., magnetic resonance spectroscopy data). It is also highly likely that MEG data are more future-proof than EEG data (higher dimensionality, ease of source localization), especially for advanced source localization methods as well as advanced analysis methods yet to be developed and applied to previously collected data. The emergence of OPM-based MEG opens a new age of imaging for children and infants, such as translating the source localizing abilities of MEG in adults to wearable systems in young children. Looking forward, greater access to MEG and other advanced imaging technologies, the accessibility of greater computational power, and the rapid development of open-source software will combine to improve our methods and inform our research questions, all leading to a better understanding of how the human brain changes and supports behavioral development from birth to adulthood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".